Data Scientist
Job Descriptions:
Partner with business stakeholders across BOL Company to solve analytical problems and support strategic decision-making.
Design and analyze experiments (A/B tests), including hypothesis formulation, metric definition, impact evaluation, and interpretation.
Develop and apply statistical and machine learning models (e.g., regression, tree-based models, forecasting) for use cases such as credit risk, default prediction, customer segmentation, and operational optimization.
Build forecasting models, including probability of default (PD) and risk scoring frameworks, to support financial and credit-related decisions.
Deliver clear, actionable insights and recommendations through presentations and stakeholder discussions.
Develop practical data science solutions, including batch processing pipelines and API-based model deployment (e.g., LLM integrations).
Manage multiple projects simultaneously in a fast-paced, dynamic environment.
Job Qualifications:
Bachelor’s or Master’s degree in Statistics, Data Science, Computer Engineering, Computer Science, Econometrics, or a related quantitative field.
At least 1 year of experience in data analytics, data science, or quantitative modeling roles (New Graduated are welcome).
Strong analytical thinking with solid business acumen.
Strong foundation in probability, statistics, machine learning, and AI.
Proficiency in SQL and Python, with strong coding skills for data manipulation, modeling, and deployment.
Experience with experimentation and A/B testing frameworks.
Experience in building predictive models, particularly in risk modeling or default probability estimation, is highly preferred.
Excellent English communication skills, with the ability to independently present and discuss insights with stakeholders.
Strong collaboration skills and ability to manage multiple priorities.
Experience in credit risk modeling, financial data science, or related domains.
Familiarity with forecasting techniques and risk scoring methodologies.
Experience in deploying AI/LLM-driven solutions in business environments.